Wyniki wyszukiwania - Biblioteka Nauki

1

Information management in passenger traffic supporting system design as a multi-criteria discrete optimization task

100%

Galuszka A. , Krystek J. , Swierniak A. , Lungoci C. , Grzejszczak T.

Archives of Control Sciences

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2017

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tom Vol. 27, no. 2

229--238

EN

This paper presents a concept of an Integrated System of Supporting Information Management in Passenger Traffic (ISSIMPT). The novelty of the system is an integration of six modules: video monitoring, counting passenger flows, dynamic information for passengers, the central processing unit, surveillance center and vehicle diagnostics into one coherent solution. Basing on expert evaluations, we propose to present configuration design problem of the system as a multi-objectives discrete static optimization problem. Then, hybrid method joining properties of weighted sum and ε-constraint methods is applied to solve the problem. Solution selections based on hybrid method, using set of exemplary cases, are shown.

2

Tuning of a fuzzy system for controlling searching process in Multi Objective Scheduling Immune Algorithm

100%

Wosik I. , Skołud B.

Journal of Machine Engineering

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2009

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tom Vol. 9, No. 1

130--143

EN

In the paper the Multi Objective Immune Algorithm (MOIA) for an open job shop scheduling problem (OJSP) is proposed. The OJSP belongs to most both time consuming and most complicated problems in scope of searching space. In the paper schedules are evaluated by using three criteria: makespan, flowtime and total tardiness. MOIA proposes a schedule, which is best one, selected from a set of achieved solutions. An affinity threshold is a parameter that controls equilibrium between searching space and solutions diversity in MOIA. The affinity threshold is defined by using fuzzy logic system. In the paper fuzzy system is tuned by selecting shape, size of fuzzy sets, and fuzzy decisions of an affinity threshold. If the fuzzy system is used then neither the knowledge about the affinity threshold nor influence over searching processes is not required from a decision-maker. The application of the fuzzy system makes the process of decision-making user friendly. In the paper efficiency of MOIA before and after the fuzzy system tuning is compared and computational results are presented

3

A Clustering Based Archive Multi Objective Gravitational Search Algorithm

88%

Abbasian M. A. , Nezamabadi-pour H. , Amoozegar M.

Fundamenta Informaticae

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2015

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tom Vol. 138, nr 4

387--409

EN

Gravitational search algorithm(GSA) is a recent createdmetaheuristic optimization algorithm with good results in function optimization as well as real world optimization problems. Many real world problems involve multiple (often conflicting) objectives, which should be optimized simultaneously. Therefore, the aim of this paper is to propose a multi-objective version of GSA, namely clustering based archive multi-objective GSA (CA-MOGSA). Proposed method is created based on the Pareto principles. Selected non-dominated solutions are stored in an external archive. To control the size of archive, the solutions with less crowding distance are removed. These strategies guarantee the elitism and diversity as two important features of multi-objective algorithms. The archive is clustered and a cluster is randomly selected for each agent to apply the gravitational force to attract it. The selection of the proper cluster is based on the distance between clusters representatives and population member (the agent). Therefore, suitable trade-off between exploration and exploitation is provided. The experimental results on eight standard benchmark functions reveal that CA-MOGSA is a well-organized multi-objective version of GSA. It is comparable with the state-ofthe- art algorithms including non-dominated sorting genetic algorithm-II (NSGA-II), strength Pareto evolutionary algorithm (SPEA2) and better than multi-objective GSA (MOGSA), time-variant particle swarm optimization (TV-PSO), and non-dominated sorting GSA (NSGSA).

4

Optimizing the performance of electrically poled polymeric films

75%

Tyagi R. , Pant M. , Singh Negi Y.

Computer Methods in Materials Science

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2015

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tom Vol. 15, No.1

127--136

EN

In this paper organic guest host system using 2-methyl-4-nitro aniline (2-MNA) as guest material and polyether sul-fone (PES) as host material is considered for analysis. Thin and transparent film samples are prepared by using different concentration of 2-MNA. To align 2-MNA molecules in the electric field direction within polymer matrix, the films are poled for half an hour by contact electrode poling technique. Conductance and dissipation factor of films are measured at room temperature by Agilent Impedance Analyzer after poling the films. Wide frequency ranges varying from 100Hz to 10M Hz are kept for optimization. The effects of chromophoric group (2-MNA) concentration on the electrical conductance and dissipation factor is analyzed. The behavior of conductance and dielectric loss arc optimized mathematically us¬ing FMINCON (a MATLAB tool) and multiobjective differential evolution algorithm (MODEA). To optimize the relation of conductance and dissipation factor with doping concentration of 2-MNA and applied frequency, the measured data is also modeled taking conductance and dissipation factor of films as dependent variable, which are affected by two independent variables namely frequency and dose of 2-MNA. The statistical validity and predictive capability of the obtained models is also checked by determining absolute average deviation and coefficients of determination.

PL

W pracy analizowano układ organiczny gospodarz-gość, składający się z aniliny 2-metylo-4-nitro (2-MNA) będącej gościem oraz polieterosulfonu (PES) będącego gospodarzem. Przygotowano cienkie i transparentne próbki filmów dla różnej koncentracji aniliny 2-MNA. W celu ułożenia molekuł 2-MNA w kierunku pola elektrycznego w matrycy polimeru, filmy pozostawały w polu elektrycznym przez pół godziny wykorzystując polaryzację elektrody. Przewodność elektryczną i czynnik rozproszenia powłok mierzono w temperaturze pokojowej analizatorem impe-dancji Agilent po procesie polaryzacji. Do optymalizacji procesu polaryzacji stosowano szeroki zakres częstotliwości od 100 Hz do 10 MHz. Analizowano wpływ koncentracji grupy chromoforowej (2 MNA) na przewodność elektryczną i czynnik rozproszenia. Zachowanie przewodności i straty dielektryczne było matema-tycznie optymalizowane z wykorzystaniem FMINCON (narzędzia MATLABa) i wielokryterialnego algorytmu ewolucji różnicowej (MODEA). Do optymalizacji relacji przewodności elektrycznej i czynnika rozproszenia z ilością substancji 2-MNA i zastosowaną częstotliwością, dane pomiarowe również były modelowane, przyjmując przewodność i czynnik rozproszenia jako wielkości zależne, będące funkcją dwóch zmiennych niezależnych: częstotliwości i ilości 2-MNA. Statystyczna istotność i możliwości przewidywania opracowanych modeli zostały także zweryfikowane poprzez określenie średniego odchylenia bezwzględnego i współczynników determinacji.

5

Obszary przewagi konkurencyjnej na rynku usług transportowych

63%

Krata P.

Logistyka

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2009

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tom nr 4

CD-CD

PL

Prezentowane dociekania teoretyczne inspirowane są teorią grawitacji rynkowej, jako interesującym elementem badań rynkowych. Rozważaniom poddano rynek usług transportowych. Zastosowany został model relacji zachodzących pomiędzy przedsiębiorstwami transportowymi i ich klientami na rynku usług transportowych, wykorzystujący do opisu cech przedsiębiorstw i klientów funkcje ciągłe o charakterze lokalnym. Umożliwiło to aplikację wybranych elementów matematycznej teorii pola. Wykorzystana wektorowa funkcja użyteczności posłużyła do wyznaczania obszarów przewagi konkurencyjnej poszczególnych przedsiębiorstw transportowych na rynku usług transportowych, przy zastosowaniu zaproponowanego algorytmu optymalizacyjnego.

EN

The theoretical consideration presented in the paper is inspired by market gravity models, as an interesting attitude towards operations research on a market. The transportation market issues are emphasized. The mathematical model of relations, taking place between transportation companies and their customers on the market, which is applied in the course of the research is based on continuous functions characteristics. This attitude enables the use of the field theory notions. The resultant vector-type utility function facilitates obtaining of competitive advantage areas for all transportation companies located on the considered transportation market.

6

A novel method for islanding in active distribution network considering distributed generation

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Wang J. , Wang X. , Di B. , Sun C. , Zheng W.

Journal of Power Technologies

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2021

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tom Vol. 101, nr 1

11--20

EN

The output of distributed generation (DG) has strong randomness, and its randomness has a great inuence on the division of islands. To simulate the impact of DG output on island division when dividing islands, this study proposed an island division method that considers the randomness of DG output. The basic idea of this method is as follows. First, Monte Carlo sampling was used to obtain the output power of DG under different confidence levels to simulate the randomness of DG output. Furthermore, a multi-objective and multi-constraint considering the randomness of DG output were established. The niche genetic algorithm was used to solve the model, and the effectiveness of the proposed model and algorithm was verified through the analysis of examples. The results show that the risk reserve power introduced by simulating the randomness of DG output is inversely proportional to the confidence level. The minimum value of the system node voltage level after islanding is 0.9495 pu, which meets the requirements of the constraint. Under the same conditions, compared with the island division method of not considering the random DG, the method proposed in this study not only has a larger total load recovery and a higher priority load recovery rate but also has a higher DG utilization rate, which can meet the needs of practical applications. This study provides a certain reference for the establishment and solution method of the islanding model of the distribution network with DG.

7

Stacking-based multi-objective evolutionary ensemble framework for prediction of diabetes mellitus

63%

Singh N. , Singh P.

Biocybernetics and Biomedical Engineering

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2020

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tom Vol. 40, no. 1

1--22

EN

Diabetes mellitus (DM) is a combination of metabolic disorders characterized by elevated blood glucose levels over a prolonged duration. Undiagnosed DM can give rise to a host of associated complications like retinopathy, nephropathy and neuropathy and other vascular abnormalities. In this background, machine learning (ML) approaches can play an essential role in the early detection, diagnosis and therapeutic monitoring of the disease. Recently, several research works have been proposed to predict the onset of DM. To this end, we develop a stacking-based evolutionary ensemble learning system ‘‘NSGA-II-Stacking’’ for predicting the onset of Type-2 diabetes mellitus (T2DM) within five years. For this purpose, publicly accessible Pima Indian diabetes (PID) dataset is utilized. As a data pre-processing step, the missing values and outliers are identified and imputed with the median values. For base learner selection, a multi-objective optimization algorithm is utilized which simultaneously maximizes the classification accuracy and minimizes the ensemble complexity. As for model combination, k-nearest neighbor (K-NN) is employed as a meta-classifier that combines the predictions of the base learners. The comparative results demonstrate that the proposed NSGA-II-Stacking method significantly outperforms several individual ML approaches and conventional ensemble approaches. In terms of performance metrics, the proposed system achieves the highest accuracy of 83.8 %, sensitivity of 96.1 %, specificity of 79.9 %, f-measure of 88.5 % and area under ROC curve of 85.9 %.

8

Parametric optimization scheme of energy dissipation and shock absorption for prefabricated concrete frame

51%

Li Z.

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2024

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tom Vol. 70, nr 2

527--541

EN

The prefabricated concrete frame structure system has advantages such as short construction period and good seismic performance, but its deformation and energy dissipation capacity are poor under earthquake action, making it prone to damage. By improving the analysis and simulation functions of existing finite element analysis for prefabricated structures, the engineering applicability of the analysis algorithm has been improved. Then, a finite element model has been established for collaborative optimization, and a parameterized optimization scheme that meets the seismic reduction requirements has been obtained. The results show that the optimization method proposed in the study has a better effect in seeking the minimum cost, and meets the design requirements of the specification. The optimization scheme of prefabricated concrete frames designed by the research institute based on finite element analysis can efficiently optimize various parameters, greatly improving the structure energy dissipation and seismic performance.